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The map shows traffic accidents recorded in Oslo, Norway, for the year 2013.

The Leaflet Markercluster plugin is wonderful. Since the markerclusters are divIcons you can put whatever you want inside them using the iconCreateFunction. I wanted my clusters to reveal more information than just the marker count and figured a pie chart would do the job. So I told the iconCreateFunction to do some D3 magic and this is the result.

The example is a bit more complicated than necessary due to how my dataset is structured. But if you take a look at the defineClusterIcon() function you'll see that I use d3.nest() to build a dataset for the pie chart based on a given property from all the cluster's children. Then I pass this dataset over to the bakeThePie() function together with instructions on how to style the chart. The function returns svg markup which in turn is placed inside the divIcon.

Feel free to suggest improvements.

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{
  "ebs_directory_path":"/___",
  "environment_variables":{
    "_________":"_________",
    "_______":"______"
  },
  "mysql":{
    "server_root_password":"_______",
    "data_dir":"_________",
    "port":"_____"

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Objective 1: Make a single request that returns an array of results, each representing a unique set of daily values.

class UserMeasurebyDay
  extend Legato::Model
  metrics :users, :new_users, :percent_new_sessions
  dimensions :date
end

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Some of these files are from the us-atlas:

• us.json - make topo/us-10m.json
• us-congress-113.json - make topo/us-congress-10m.json

Others are from the world-atlas:

• world-50m.json - make topo/world-50m.json
• world-110m.json - make topo/world-110m.json

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{"type":"MultiPolygon","coordinates":[[[[-155.59,20.14],[-155.58,20.13],[-155.57,20.13],[-155.56,20.14],[-155.55,20.14],[-155.53,20.14],[-155.49,20.11],[-155.45,20.11],[-155.34,20.06],[-155.21,20],[-155.17,19.97],[-155.09,19.88],[-155.08,19.87],[-155.08,19.84],[-155.08,19.77],[-155.07,19.74],[-155.06,19.74],[-155.02,19.75],[-154.99,19.74],[-154.98,19.73],[-154.98,19.72],[-154.97,19.67],[-154.96,19.65],[-154.92,19.61],[-154.87,19.59],[-154.79,19.54],[-154.8,19.52],[-154.81,19.5],[-154.82,19.48],[-154.83,19.46],[-154.91,19.42],[-154.92,19.41],[-155.01,19.33],[-155.02,19.33],[-155.05,19.32],[-155.07,19.32],[-155.1,19.3],[-155.17,19.28],[-155.19,19.28],[-155.27,19.28],[-155.29,19.27],[-155.3,19.27],[-155.32,19.25],[-155.35,19.22],[-155.37,19.22],[-155.38,19.21],[-155.4,19.2],[-155.42,19.18],[-155.44,19.17],[-155.49,19.14],[-155.5,19.14],[-155.55,19.1],[-155.55,19.08],[-155.57,19.03],[-155.61,18.97],[-155.63,18.96],[-155.64,18.95],[-155.66,18.93],[-155.67,18.93],[-155.67,18.94],[-155.69,18.96],[-155.71,18.99],[-15

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These county, state and country boundaries are extracted from a single TopoJSON file. Counties are stroked in thin gray, states in thin black, and the country in thick black.

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Some of these files are from the us-atlas:

• us.json - make topo/us-10m.json
• us-congress-113.json - make topo/us-congress-10m.json

Others are from the world-atlas:

• world-50m.json - make topo/world-50m.json
• world-110m.json - make topo/world-110m.json

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This is the map of Nielen Designated Marketing Areas using D3.js. Hover over for data related to each area.

See map here

###Credits

• Map adapted from Mike Bostock's map example
• Topojson made by converting shapefile from here to topojson via Mike Bostock's instructions
• Nielsen rank and TV data via tvb

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find . -name "*passenger*" -print